01
Why did AI spend jump?
Finance has vendor invoices, card charges, and budget variance.
Map spend to employees, teams, tools, API keys, and workflows.When the CFO asks why AI spend jumped, bring names.
A 10-business-day audit for CIOs and IT leaders who need a defensible AI spend answer now. We stitch invoices, vendor usage, identity, SSO, and security signals into one memo: who drove spend, what is waste, what is risky, and which repeated tasks should become governed workflows.
No prompt text. No message content. Usage metadata, invoices, and employee/team mapping only.
Claude CodeCodexCursorGitHub CopilotChatGPTGeminiOpenAI APIAnthropic APIInternal agents
First read24 hours
Full audit10 business days
Prompt contentNot required
OutputCut / cap / govern / automate
Buyer moment
When the CFO asks, eight AI dashboards are not an answer.
The first customer is the CIO or IT leader who already knows AI usage is spreading, but cannot yet defend the bill, identify the waste, or tell security which behavior needs policy.
02
Which usage is worth keeping?
IT can see who has access, not whether the usage is productive.
Separate approved work, repeated manual tasks, unused seats, and expensive model choices.03
Where are we exposed?
Security sees AI domains, but not the business owner or spend context.
Flag unmanaged personal AI, sensitive departments, orphaned keys, and ex-employee access.The failure mode
Every team sees a slice. Nobody owns the answer.
01
Finance has invoices, not attribution.
The CFO sees Anthropic, OpenAI, Cursor, Copilot, and card spend. They cannot split it by employee, team, API key, or workflow.
02
IT has access, not usage quality.
Okta and Entra show who can log in. They do not show whether the usage is valuable, wasteful, duplicated, or unmanaged.
03
Security has domain logs, not business context.
Personal ChatGPT and Claude traffic appears in network tools, but it is hard to connect that signal to teams, spend, and policy actions.
04
AI owners see experiments, not repeatable workflows.
Employees repeat the same prompts thousands of times. Nobody knows which ones should become approved internal agents.
Data room
We build the AI bill of materials.
Vendor usage
ChatGPT, Claude, OpenAI, Anthropic, Cursor, Copilot, Gemini exports
Identity map
Employee directory, department, manager, cost center, contractor status
Finance records
Invoices, AP records, card spend, procurement contracts, renewal dates
Access signals
Okta, Entra, Google Workspace, SSO login events, SCIM assignments
Risk signals
Optional Zscaler, Netskope, Cloudflare, Defender, browser or endpoint logs
Internal AI
API keys, gateways, internal agents, project metadata, model usage
First 24 hours
Give the CIO a first answer before the full cleanup is done.
The first read is intentionally imperfect but useful: total spend, biggest owner gaps, obvious waste, risk signals, missing data, and the three questions the customer has to answer next.
Initial AI spend findingsAcme Corp / May snapshot
24h readTotal AI spend last month$142,300
Forecasted month-end spend$188,000
Spend without clear owner$31,400
Monthly savings identified$42,000
Missing data: GitHub Copilot export, SSO file upload event logs, API key owner map.
Final audit
What you get in 10 business days.
01
AI spend by vendor, team, user, project, and workflow
02
Top expensive users, API keys, apps, and model switches
03
Unused seats, duplicate subscriptions, and ex-employee access
04
Sensitive team usage and unmanaged personal AI signals
05
Repeated AI tasks that should become approved internal workflows
06
Savings plan: what to cut, cap, route cheaper, block, or automate
07
Executive readout your CIO can use with Finance, IT, Security, and AI leaders
Action ledgerWhat to cut, cap, govern, or automate
ActionSignalImpactOwner
Remove inactive seatsChatGPT + Cursor$4.1k/moIT
Reassign orphaned keysAnthropic API$4.2k/mo at riskEng Ops
Route simple summaries cheaperSupport AI workflow$9.8k/moAI Platform
Block personal AI in LegalChatGPT / Claude webHigh riskSecurity
Build Zendesk summarizer18,400 runs/mo1,400 hrs/moSupport Ops
How it starts
Manual enough to learn. Structured enough to repeat.
First-read memo
Spend totals, missing data, obvious waste, owner gaps, and the first CFO answer.
Evidence stitching
Normalize invoices, usage exports, SSO, directory, access logs, and cost centers.
Action ledger
Prioritize seat cuts, key ownership, model routing, risky teams, and workflows to automate.
Executive readout
CIO-ready narrative, spreadsheet, source map, and next 30-day operating plan.
Paid audit
Start with exports. Earn the right to become software.
This should not begin with a six-month integration project. Send invoices, usage exports, employee/team mapping, and SSO app data. We return the action plan first, then productize the repeated ingestion once the pain is proven.